Python · Introduction to Machine Learning — Statistical Foundations

Introduction

What this guide covers

Introduction Chart from the original guide Python · Applied statistics

Overview

Topics covered

• Introduction
• Introduction to Machine Learning from statistical foundations
• Definition and taxonomy of Machine Learning
• 1.1 Fundamental taxonomy: three learning paradigms
• Supervised learning Supervised
• Unsupervised learning Unsupervised

Related concepts

Main connections

• Regularization (Lasso / Ridge / Elastic Net)
• Variance & standard deviation
• Preprocessing pipelines & transform recipes
• Overfitting & cross-validation
• Linear algebra & matrices
• Logistic regression

Compatible notation

Mathematical sample in LaTeX

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